Evolutionary Computation Technical Committee : Games Working Group

Games provide competitive dynamic environments that make
ideal test-beds for computational intelligence theories, architectures,
and algorithms. Natural evolution can be considered a game, where the
rewards for an organism that plays a good game of life are the propagation
of its genetic material to its successors. In natural evolution, the
fitness of an individual is defined with respect to its competitors and
collaborators, as well as the environment. Within the evolutionary
computation (EC) literature, this is known as co-evolution, and within this
paradigm expert game-playing strategies have been evolved without the need
for human expertise.

Much of the early work on computational intelligence and
games was directed towards classic board games, such as tic-tac-toe
(noughts and crosses), chess, and checkers (draughts), but in most board
games, computers now far out-class human players. A game that has so
far resisted machine attack is Go, where the best computer players now play at the
level of a good novice. Go strategy seems to rely as much on pattern
recognition as it does on logical analysis, and the large branching
factor severely restricts the look-ahead that can be used within a
game-tree search.

Games also provide interesting abstractions of real-world
situations, a classic example being Axelrod's
Prisoner's
Dilemma. Of particular interest to the computational
intelligence community, is the iterated version of this game (IPD), where
plays can devise strategies that depend on previous behaviour. A
version of IPD was run as a competition for 2004 Congress on Evolutionary
Computation, and a different version will be used for the
CIG 2005 competition.

In recent years, researchers have been applying EC
methods to evolving all kinds of game-players, including real-time arcade
and console games (e.g. Quake, Pac-Man). There are many goals to
this research, and one emerging theme is using EC to generate opponents
that are more interesting and fun to play against, rather than being
necessarily superior.

This working group is dedicated to promoting all types of
interplay between games and evolutionary computation.